1. Field of the Invention
The present invention relates in general to noise reduction or removal from compressed video images, and more particularly to reduction or outright removal of block artifacts that are associated with block-based compression/coding schemes.
2. Description of the Related Technology
As demonstrated by the near-universal application of the MPEG algorithm, block transform coding based on the discrete cosine transform is a proven method for image compression. The method divides images into blocks and then treats each block independently, applying a numerical transform to the blocks, quantizing the transform coefficients and then efficiently encoding the string of coefficients. Currently, Digital TV (DTV) broadcasting in the U.S. uses the MPEG-2 international video compression standard to compress digital video content. DVD video content may be processed using the MPEG-2, MPEG-4, or H.264 standards.
These are block based algorithms. Block based video compression introduces artifacts that deteriorate the quality of the displayed video images and scenes; the artifacts in MPEG-processed digital videos are often referred to as “MPEG noise”, or “compression noise.” Compression noise reduction is the process that detects and removes or reduces the imperfections introduced by MPEG from the digital video images before displaying the recovered video.
The artifacts appear as undesired spurious edges or discontinuities at block boundaries in images. They arise as stated above in images and videos that are compressed by block-based coding schemes such as JPEG, MPEG, and H.26X. In these coding techniques, a picture is divided into an array of N-by-N rectangular blocks of pixels (the number of pixels N is usually 16) that are called macroblocks. Then, each macroblock is again sub-divided into M-by-M pixels (M is usually 8) sub-blocks. Each sub-block is typically processed by an 8-by-8 discrete cosine transform (DCT) into an array of 8×8 coefficients; these are quantized with a block size that may vary from block to block. That is the coefficients may be binned into a smaller set of values thus reducing the number of required bits for each coefficient. The quantized coefficients are scanned in a zig-zag pattern to reduce them to a one-dimensional string and the string of coefficients is then entropy encoded. Each sub-block is processed independently of other sub-blocks.
Because each sub-block is processed independently of all others, a critical portion of the video image data that connects neighboring blocks may be lost, leading to superfluous edges and artificial discontinuities appearing at the block boundaries. Block artifacts become more noticeable as the image/video is compressed more, i.e., at higher compression ratios that require increasing the quantization block size to reduce the data rate at the compression unit's output.
Approaches for reducing compression noise involve estimating the artifact strength and reducing the artifacts according to the measured results. Block artifacts appear with varying strengths at the boundaries of sub-blocks within a coded image. If a fixed non-adaptive de-blocking filter were uniformly applied to all block boundaries, either the strong block artifacts would not be adequately reduced or fine image features would be blurred due to over smoothing. Therefore a technique for correcting the artifact is needed which adapts to the strength of the artifacts to be corrected and the activity in the video data that surrounds it.